Razvan Pascanu

According to our database1, Razvan Pascanu authored at least 92 papers between 2010 and 2019.

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Bibliography

2019
Meta-Learning with Warped Gradient Descent.
CoRR, 2019

Task Agnostic Continual Learning via Meta Learning.
CoRR, 2019

Meta-learning of Sequential Strategies.
CoRR, 2019

Information asymmetry in KL-regularized RL.
CoRR, 2019

Ray Interference: a Source of Plateaus in Deep Reinforcement Learning.
CoRR, 2019

A RAD approach to deep mixture models.
CoRR, 2019

Exploiting Hierarchy for Learning and Transfer in KL-regularized RL.
CoRR, 2019

Distilling Policy Distillation.
CoRR, 2019

Functional Regularisation for Continual Learning using Gaussian Processes.
CoRR, 2019

Deep reinforcement learning with relational inductive biases.
Proceedings of the 7th International Conference on Learning Representations, 2019

Meta-Learning with Latent Embedding Optimization.
Proceedings of the 7th International Conference on Learning Representations, 2019

Hyperbolic Attention Networks.
Proceedings of the 7th International Conference on Learning Representations, 2019

Information asymmetry in KL-regularized RL.
Proceedings of the 7th International Conference on Learning Representations, 2019

A RAD approach to deep mixture models.
Proceedings of the Deep Generative Models for Highly Structured Data, 2019

Distilling Policy Distillation.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
Adapting Auxiliary Losses Using Gradient Similarity.
CoRR, 2018

Meta-Learning with Latent Embedding Optimization.
CoRR, 2018

Relational Deep Reinforcement Learning.
CoRR, 2018

Relational recurrent neural networks.
CoRR, 2018

Mix&Match - Agent Curricula for Reinforcement Learning.
CoRR, 2018

Relational inductive biases, deep learning, and graph networks.
CoRR, 2018

Hyperbolic Attention Networks.
CoRR, 2018

Been There, Done That: Meta-Learning with Episodic Recall.
CoRR, 2018

Progress & Compress: A scalable framework for continual learning.
CoRR, 2018

Low-pass Recurrent Neural Networks - A memory architecture for longer-term correlation discovery.
CoRR, 2018

Block Mean Approximation for Efficient Second Order Optimization.
CoRR, 2018

Learning Deep Generative Models of Graphs.
CoRR, 2018

Memory-based Parameter Adaptation.
CoRR, 2018

Model compression via distillation and quantization.
CoRR, 2018

Relational recurrent neural networks.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Progress & Compress: A scalable framework for continual learning.
Proceedings of the 35th International Conference on Machine Learning, 2018

Been There, Done That: Meta-Learning with Episodic Recall.
Proceedings of the 35th International Conference on Machine Learning, 2018

Mix & Match Agent Curricula for Reinforcement Learning.
Proceedings of the 35th International Conference on Machine Learning, 2018

Memory-based Parameter Adaptation.
Proceedings of the 6th International Conference on Learning Representations, 2018

Model compression via distillation and quantization.
Proceedings of the 6th International Conference on Learning Representations, 2018

2017
Imagination-Augmented Agents for Deep Reinforcement Learning.
CoRR, 2017

Visual Interaction Networks.
CoRR, 2017

Distral: Robust Multitask Reinforcement Learning.
CoRR, 2017

A simple neural network module for relational reasoning.
CoRR, 2017

Discovering objects and their relations from entangled scene representations.
CoRR, 2017

Learning model-based planning from scratch.
CoRR, 2017

Metacontrol for Adaptive Imagination-Based Optimization.
CoRR, 2017

Sharp Minima Can Generalize For Deep Nets.
CoRR, 2017

Sobolev Training for Neural Networks.
CoRR, 2017

Visual Interaction Networks: Learning a Physics Simulator from Video.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Distral: Robust multitask reinforcement learning.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

A simple neural network module for relational reasoning.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Imagination-Augmented Agents for Deep Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Sobolev Training for Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Sharp Minima Can Generalize For Deep Nets.
Proceedings of the 34th International Conference on Machine Learning, 2017

Discovering objects and their relations from entangled scene representations.
Proceedings of the 5th International Conference on Learning Representations, 2017

Learning to Navigate in Complex Environments.
Proceedings of the 5th International Conference on Learning Representations, 2017

Metacontrol for Adaptive Imagination-Based Optimization.
Proceedings of the 5th International Conference on Learning Representations, 2017

Sim-to-Real Robot Learning from Pixels with Progressive Nets.
Proceedings of the 1st Annual Conference on Robot Learning, CoRL 2017, Mountain View, 2017

2016
Local minima in training of deep networks.
CoRR, 2016

Sim-to-Real Robot Learning from Pixels with Progressive Nets.
CoRR, 2016

Progressive Neural Networks.
CoRR, 2016

Policy Distillation.
Proceedings of the 4th International Conference on Learning Representations, 2016

Learning to Navigate in Complex Environments.
CoRR, 2016

Overcoming catastrophic forgetting in neural networks.
CoRR, 2016

Interaction Networks for Learning about Objects, Relations and Physics.
CoRR, 2016

Theano: A Python framework for fast computation of mathematical expressions.
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CoRR, 2016

Interaction Networks for Learning about Objects, Relations and Physics.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2015
Natural Neural Networks.
CoRR, 2015

Natural Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Malware classification with recurrent networks.
Proceedings of the 2015 IEEE International Conference on Acoustics, 2015

2014
Revisiting Natural Gradient for Deep Networks
Proceedings of the 2nd International Conference on Learning Representations, 2014

On the number of inference regions of deep feed forward networks with piece-wise linear activations.
Proceedings of the 2nd International Conference on Learning Representations, 2014

How to Construct Deep Recurrent Neural Networks.
Proceedings of the 2nd International Conference on Learning Representations, 2014

On the saddle point problem for non-convex optimization.
CoRR, 2014

On the Number of Linear Regions of Deep Neural Networks.
CoRR, 2014

Identifying and attacking the saddle point problem in high-dimensional non-convex optimization.
CoRR, 2014

Learned-Norm Pooling for Deep Feedforward and Recurrent Neural Networks.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2014

On the Number of Linear Regions of Deep Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Identifying and attacking the saddle point problem in high-dimensional non-convex optimization.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

2013
Natural Gradient Revisited
Proceedings of the 1st International Conference on Learning Representations, 2013

Metric-Free Natural Gradient for Joint-Training of Boltzmann Machines
Proceedings of the 1st International Conference on Learning Representations, 2013

Learned-norm pooling for deep neural networks.
CoRR, 2013

Pylearn2: a machine learning research library.
CoRR, 2013

On the difficulty of training recurrent neural networks.
Proceedings of the 30th International Conference on Machine Learning, 2013


Advances in optimizing recurrent networks.
Proceedings of the IEEE International Conference on Acoustics, 2013

2012
Learning Algorithms for the Classification Restricted Boltzmann Machine.
J. Mach. Learn. Res., 2012

Advances in Optimizing Recurrent Networks
CoRR, 2012

Theano: new features and speed improvements
CoRR, 2012

Understanding the exploding gradient problem
CoRR, 2012

2011
Contextual tag inference.
TOMCCAP, 2011

A neurodynamical model for working memory.
Neural Networks, 2011

Deep Learners Benefit More from Out-of-Distribution Examples.
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, 2011

Autotagging music with conditional restricted Boltzmann machines
CoRR, 2011

2010
Deep Self-Taught Learning for Handwritten Character Recognition
CoRR, 2010

Extraction of quadrics from noisy point-clouds using a sensor noise model.
Proceedings of the IEEE International Conference on Robotics and Automation, 2010


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